The telecom industry stands at a pivotal moment of transformation. As mobile network operators grapple with the challenges of creating new revenue streams, artificial intelligence (AI) has emerged as an enabler of next-generation capabilities.
The recent Juniper Research worldwide market study illuminates how AI is not merely an add-on but increasingly the foundation of transformative cellular network evolution.
According to the study, network operators are projected to invest more than $86 billion in developing and deploying AI in their platforms over the next four years.
Mobile Network AI Market Development
Annual investment is expected to grow from $13.5 billion in 2025 to $21.9 billion by 2029, representing a substantial 62 percent increase.
This investment surge is primarily driven by operators' pursuit of zero-touch operations, where human intervention in network management is minimized or eliminated entirely.
What's particularly notable is that while AI is being deployed across multiple operator domains – from Business Support Systems (BSS) to enterprise offerings – the network infrastructure represents the area where AI can deliver the most significant impact.
This focus makes strategic sense, as network infrastructure accounts for the majority of a mobile network provider's capital and operating expenditure.
Three clear trends are driving this investment trajectory:
- Despite the growth of 5G connections from 255 million in 2020 to a projected 2.8 billion in 2025 (and 6.5 billion by 2029), operators have struggled to identify a use case that justifies the massive investments.
- With 39 percent of operators committed to net-zero targets, representing 43 percent of global telecom revenue, energy efficiency is a primary focus.
- AI is enabling operators to develop more diversified business models, with services like network slicing that provide differentiated connectivity.
Several trends will define the evolution of AI in cellular networks:
- Agentic AI represents perhaps the most transformative development. These systems can autonomously make decisions based on defined parameters and execute network functions without human intervention. Implementing agentic AI in the Radio Access Network (RAN) offers the most immediate ROI potential for operators, with significant improvements in real-time optimization and latency reduction.
- Digital Twins will become increasingly important as operators seek to create accurate digital models of their physical infrastructure. These virtual representations enable sophisticated simulation, testing, and monitoring capabilities that inform AI-based network orchestration decisions.
- Federated Learning offers a promising approach to efficiently train new AI models across distributed networks without compromising data privacy or security. By training models at the edge rather than centralizing data, operators can reduce communication expenditure while maintaining effectiveness.
- Network Slicing will finally become commercially viable through AI automation, allowing operators to efficiently create, configure and manage multiple logical networks on shared physical infrastructure. The key to monetization will be integrating these services into end-to-end industry-specific solutions rather than offering them as standalone connectivity options.
The savvy mobile network operators that succeed in this new marketplace will be those that view AI as a cost-cutting tool and as a strategic enabler of new business models.
Outlook for AI Applications Demand in Telecom
While the immediate benefits of energy efficiency and TCO reduction are compelling, the long-term value lies in the ability of AI to transform how networks function – creating more responsive, resilient, and revenue-generating infrastructure.
"Despite the significant amount operators will invest, the cost savings arising from the reduced energy consumption enabled by implementing Agentic AI in RANs is expected to be a substantial contributor to operators achieving ROI," said Alex Webb, senior research analyst at Juniper Research.
For telecom companies navigating this transition, the message is clear. I believe AI is no longer optional but essential to competitive survival. Those forward-thinking network operators who invest strategically now will position themselves to lead where applied-AI use cases are a catalyst for new business models and associated revenue growth.